These are suggestions for papers to present in the reading group.
✅ Roth, J. and Sant’Anna, P.H.C. (2023). “When Is Parallel Trends Sensitive to Functional Form?” Econometrica, 91(2), 737–747. link
✅ Tazhitdinova, A. and Vazquez-Bare, G. (2023). “Difference-in-Differences with Unequal Baseline Treatment Status.” NBER Working Paper 31063. link
Chiu, A., Lan, X., Liu, Z., and Xu, Y. (2024). “Causal Panel Analysis under Parallel Trends: Lessons from a Large Reanalysis Study.” American Political Science Review, 120(1), 245–266. link
Arkhangelsky, D. and Imbens, G.W. (2024). “Causal Models for Longitudinal and Panel Data: A Survey.” The Econometrics Journal, 27(3), C1–C61. link
Manski, C.F. and Pepper, J.V. (2018). “How Do Right-to-Carry Laws Affect Crime Rates? Coping with Ambiguity Using Bounded-Variation Assumptions.” Review of Economics and Statistics, 100(2), 232–244. link
Rambachan, A. and Roth, J. (2023). “A More Credible Approach to Parallel Trends.” Review of Economic Studies, 90(5), 2555–2591. link
Arkhangelsky, D., Athey, S., Hirshberg, D.A., Imbens, G.W., and Wager, S. (2021). “Synthetic Difference-in-Differences.” American Economic Review, 111(12), 4088–4118. link
Arkhangelsky, D. and Imbens, G.W. (2022). “Doubly Robust Identification for Causal Panel Data Models.” The Econometrics Journal, 25(3), 649–674. link
✅ Gunsilius, F. (2023). “Distributional Synthetic Controls.” Econometrica, 91(3), 1105–1117. link
Callaway, B. and Tsyawo, E.S. (2023). “Treatment Effects in Staggered Adoption Designs with Non-Parallel Trends.” arXiv:2308.02899. link
Arkhangelsky, D. and Imbens, G.W. (2024). “Fixed Effects and the Generalized Mundlak Estimator.” Review of Economic Studies, 91(5), 2545–2571. link
Arkhangelsky, D., Imbens, G.W., Lei, L., and Luo, X. (2024). “Design-Robust Two-Way-Fixed-Effects Regression for Panel Data.” Quantitative Economics, 15(4), 999–1034. link
Sun, Y., Xie, H., and Zhang, Y. (2025). “Difference-in-Differences Meets Synthetic Control: Doubly Robust Identification and Estimation.” arXiv:2503.11375. link
✅ Rincón, R. and Song, K. (2025). “Causal Inference with Groupwise Matching.” arXiv:2510.26106. link
✅ Athey, S., Imbens, G.W., Qu, Z., and Viviano, D. (2025). “Triply Robust Panel Estimators.” arXiv:2508.21536. link
Liu, Y. (2025). “Synthetic Parallel Trends.” arXiv:2511.05870. link
Callaway, B., Dyal, D., Sant’Anna, P.H.C., and Tsyawo, E.S. (2025). “Beyond Parallel Trends: An Identification-Strategy-Robust Approach to Causal Inference with Panel Data.” arXiv:2511.21977. link
✅ Ashenfelter, O. and Card, D. (1985). “Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs.” Review of Economics and Statistics, 67(4), 648-660. link *
✅ Heckman, J.J. and Hotz, V.J. (1989). “Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The Case of Manpower Training.” Journal of the American Statistical Association, 84(408), 862–874. link *
✅ Card, D. (1990). “The Impact of the Mariel Boatlift on the Miami Labor Market.” Industrial and Labor Relations Review, 43(2), 245-257. link †
✅ Card, D. and Krueger, A.B. (1994). “Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania.” American Economic Review, 84(4), 772-793. link *
✅ Meyer, B.D. (1995). “Natural and Quasi-Experiments in Economics.” Journal of Business and Economic Statistics, 13(2), 151-161. link †
Blundell, R. and Costa Dias, M. (2000). “Evaluation Methods for Non-Experimental Data.” Fiscal Studies, 21(4), 427-468. link
Angrist, J.D. and Pischke, J.S. (2009). Mostly Harmless Econometrics: An Empiricist’s Companion, Chapter 5: “Parallel Worlds: Fixed Effects, Difference-in-Differences, and Panel Data.” Princeton University Press.
✅ Imbens, G.W. and Wooldridge, J.M. (2009). “Recent Developments in the Econometrics of Program Evaluation.” Journal of Economic Literature, 47(1), 5-86. link
✅ Lechner, M. (2011). “The Estimation of Causal Effects by Difference-in-Difference Methods.” Foundations and Trends in Econometrics, 4(3), 165-224. link †
Ghanem, D., Sant’Anna, P.H.C., and Wuthrich, K. (2022). “Selection and Parallel Trends.” SSRN. link
Heckman, J.J., Ichimura, H., Smith, J., and Todd, P. (1997). “Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme.” Review of Economic Studies, 64(4), 605-654. link
Abadie, A. (2005). “Semiparametric Difference-in-Differences Estimators.” Review of Economic Studies, 72(1), 1-19. link
Sant’Anna, P.H.C. and Zhao, J. (2020). “Doubly Robust Difference-in-Differences Estimators.” Journal of Econometrics, 219(1), 101–122. link
Caetano, C. and Callaway, B. (2024). “Difference-in-Differences when Parallel Trends Holds Conditional on Covariates.” arXiv:2406.15288. link
Abadie, A., Diamond, A., and Hainmueller, J. (2010). “Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program.” Journal of the American Statistical Association, 105(490), 493–505. link
Sun, L., Ben-Michael, E., and Feller, A. (2025). “Using Multiple Outcomes to Improve the Synthetic Control Method.” Review of Economics and Statistics. link
Arkhangelsky, D. and Hirshberg, D. (2023). “Large-Sample Properties of the Synthetic Control Method under Selection on Unobservables.” arXiv:2311.13575. link
Athey, S., Bayati, M., Doudchenko, N., Imbens, G.W., and Mackey, L. (2021). “Matrix Completion Methods for Causal Panel Data Models.” Journal of the American Statistical Association, 116(536), 1770–1788. link
Abadie, A. (2021). “Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects.” Journal of Economic Literature, 59(2), 391–425. link
Ben-Michael, E., Feller, A., and Rothstein, J. (2021). “The Augmented Synthetic Control Method.” Journal of the American Statistical Association, 116(536), 1789–1803. link
Doudchenko, N. and Imbens, G.W. (2016). “Balancing, Regression, Difference-in-Differences and Synthetic Control Methods: A Synthesis.” NBER Working Paper 22791. link
Ferman, B. and Pinto, C. (2021). “Synthetic Controls with Imperfect Pre-Treatment Fit.” Quantitative Economics, 12(4), 1197–1221. link
Imbens, G.W. and Viviano, D. (2023). “Identification and Inference for Synthetic Controls with Confounding.” arXiv:2312.00955. link
Kellogg, M., Mogstad, M., Pouliot, G., and Torgovitsky, A. (2021). “Combining Matching and Synthetic Control to Trade off Biases from Extrapolation and Interpolation.” Journal of the American Statistical Association, 116(536), 1804–1816. link